1. Technical Field of the Invention
This invention relates to a magnetic resonance spectroscopic imaging (MRSI) method, specifically to a magnetic resonance spectroscopic imaging method with up to three spatial dimensions and one spectral dimension. The method employs sparse spectral sampling with controlled spectral aliasing and nonlinear sampling density to maximize encoding speed, data sampling efficiency and sensitivity, and to interleave additional spatial-spectral encoding into the spectroscopic encoding scheme. A preferred use is the interleaving of dynamically switched magnetic field gradients to enables multi-region shimming in a single shot to compensate the spatially varying spectral line broadening resulting from local magnetic field gradients.
2. Description of the Prior Art
Sparse spectral and spatial sampling in MR spectroscopy and spectroscopic imaging
In MR spectroscopy (MRS) data sampling is equidistant in time to enable spectral reconstruction using the Fast Fourier Transform technique. The need to reduce data acquisition times of multidimensional NMR spectroscopy experiments has fostered considerable interest in novel data acquisition schemes (1-5). A recurring theme is that of reduced dimensionality experiments, in which time evolutions in the indirect dimensions are incremented together, rather than independently. Spectral analysis of such data is carried out using methods such as filtered backprojection, Generalized Fourier Transform, or parametric signal modeling. Such sparse data sampling methods are particularly advantageous in multidimensional NMR spectroscopy of complex bio-molecules. However, sparse spectral sampling in the primary spectral dimension has not been used so far, since there is no apparent benefit.
A class of spectroscopic imaging techniques, called SLIM (6) and SLOOP (7), uses anatomical information (e.g. using high resolution MRI) to define the shape of compartments with a spatially homogeneous spectral composition. This prior information is used to select phase encoding steps for spatial encoding to achieve the desired spatial response profile. Depending on the shape and number of compartments, this method can substantially reduce the number of phase encoding steps as compared to conventional phase encoding. In theory this approach allows super-resolution, i.e. no contamination between spectra from different compartments. However, SLIM is susceptible to inhomogeneities inside the chosen compartments, e.g. due to susceptibility and shimming, or due to different chemical species. These may lead to spectral contamination from neighboring compartments. SLOOP minimizes this effect by matching the point spread function to the shape of each compartment. Global optimization of localization scheme, i.e. optimal choice of phase encoding steps, remains a challenge. An alternative sparse k-space encoding has recently been described by Gao et al. (8). These methods are not widely used due to the complexity of designing optimal k-space trajectories and due to the fact that in clinical imaging applications the high-resolution MRI scans may only provide a biased reference for choosing compartments as biochemistry may change across space independently of the NMR properties of water.
High-Speed MR Spectroscopic Imaging:
High speed MRSI integrates spatial encoding modules into the spectral acquisition. We have developed Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI) which employs echo-planar readout gradients to accelerate spatial encoding times by more than one order of magnitude as compared to conventional techniques to measure 2-dimensional metabolite distributions at short TE and 3-dimensional metabolite distributions (9,10). PEPSI has also been employed for time-resolved metabolic imaging to dynamically map lactate concentrations during respiratory and metabolic challenges (11,12), to characterize metabolic dysfunction during sodium-lactate infusion in patients with panic disorder (13) and to map multiplet resonance in human brain at short echo time and high field strength (14). We have further increased the encoding speed of high-speed MRSI by combining Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI) with parallel imaging to obtain up to 4-fold acceleration and measurement times of 16 s for a 32×32 matrix with TR 2 s (15) on a 4 Tesla scanner. This technology is particularly advantageous for 3-dimensional spatial mapping and further improvement in encoding efficiency enabled single-shot MRSI (16) in our laboratory.
Sparse spectral sampling has not yet been applied to MR spectroscopic imaging and localized MR spectroscopy. However, high-speed spectroscopic imaging makes the use of sparse spectral sampling useful, since it enables flexible trade-off between spectral and spatial sampling density for the purpose of accelerating spatial and spectral sampling. A major limitation of interleaved spatial-spectral encoding is the limited spectral bandwidth that can be achieved in a single excitation due to magnetic field gradient constraints. This leads to spectral aliasing, which current methodology compensates by spectral interleaving. Furthermore, integration of spatial encoding in a second and third spatial dimension during the spectroscopic acquisition is highly desirable, but this leads to even more severe spectral aliasing and this approach is limited by magnetic field gradient performance. As a consequence, MRSI techniques are very sensitive to movement and mapping of dynamically changing spectral patterns will lead to spatial and spectral blurring of the spectroscopic images. Encoding of large spatial matrices and 3-dimensional spatial encoding are very time consuming, even with high-speed MRSI methods.
Compensation of Magnetic Field Inhomogeneity
Magnetic resonance spectroscopic imaging and localized spectroscopy in vivo suffer from microscopic and macroscopic magnetic field inhomogeneity that broaden spectral lines, reduce sensitivity and impair spectral fitting. This is one of the major limitations of MRSI in vivo. Conventional means of compensating such inhomogeneity include: (a) shimming, which is limited to low shim coils with spatial frequencies and therefore not very effective over large volumes (b) separate acquisition of multiple volumes with different shim settings, which is time consuming (c) increasing spatial resolution, which is very costly in terms of sensitivity and increases measurement time.
Inhomogeneity of the static magnetic field (B0) can be as large as 6 parts-per-million (ppm) across the brain (17,18). These spatial nonlinearities of local gradients are an important limiting factor in volumetric MRSI studies. Higher order auto-shimming (HOAS) provided on most high-field scanners offers limited capability for correction of such imperfections. While all MR processes will benefit from improved shimming to some degree, specific regions of clinical interest, such as the frontal and medial-temporal brain regions, and acquisition techniques, such as MRSI, can be critically affected by shimming effectiveness. In the case of MRSI, shim state can adversely affect spectral line width, causing artifactual frequency shifts between voxels and decrease effectiveness of water suppression. Furthermore, poorly suppressed water signal can alias into regions of otherwise adequate water suppression as a result of subject motion or k-space undersampling, causing baseline artifact. Aliasing of residual water signals from regions outside of the volume of interest is particularly difficult to identify.
HOAS typically uses a collection of shim coils based on spherical harmonics or other spatial shapes (for a review, see (19)). These coils are powered by current-feedback amplifiers under the control of a user-addressable interface and analysis program. The corrective fields generated by the coils are of finite number, power and extent. Due to time constraints, HOAS attempts to converge to an optimum shim state analytically rather than iteratively, using field maps collected with the existing imaging capability (20-24). Progress in improving existing technique has focused on addressing the limits of the shimming hardware (25-30) and accuracy and stability of the analysis (31,32). However, for spectroscopic imaging the performance of HOAS is still insufficient, in particular at high field.
To overcome large local disturbances in field homogeneity, several methods for correction have been proposed. The use of additional passive ferromagnetic shims in a cylindrical array, placed in close proximity to the human head, has been demonstrated (25). Mouthpieces containing diamagnetic shim material (passive shims) have been developed to enhance the B0 homogeneity of the mesioinferior frontal lobes (26,27). Hsu and Glover (28) have taken a similar approach but have used a mouthpiece than contains an active shim coil. However, for clinical applications of spectroscopic imaging these approaches are not practical.
Extending the capability of the existing field coil design requires either more coils of higher order (29), or better control over the existing coils. To increase control, Blamire and colleagues (33) showed that a dynamic shim state, following the current acquisition slice, can improve the corrective power of the shim coils by reducing the spatial constraints on the shim state. Subsequent studies have further demonstrated its effectiveness (34). Dynamic shimming offers greater flexibility in compensating local magnetic field distortion, but applications are currently limited by the considerable hardware demands. However, the clinical manufacturers have identified dynamically switched higher order shims as an important advance and have started product development. It is thus foreseeable that switching higher order shims will become clinical routine.
Another form of dynamic shimming is the integration of pulsed shim gradient into the MR pulse sequence to compensate local magnetic field inhomogeneity at a particular echo time within the pulse sequence. In the fMRI literature single- and multi-shot gradient compensation schemes, such as Z-shimming (35) or multi-echo EPI (36) with interleaved gradient compensation have shown significant signal recovery in frontal and medial temporal regions. This latter approach has neither been applied to conventional MRS nor to MRSI. As a consequence, conventional methods to minimize the effects of local magnetic field inhomogeneity on spectral line width in MRSI require elongation of the measurement time or sacrificing signal-to-noise per unit time. Despite best efforts, these approaches are still limited and MRSI of the entire brain remains an elusive goal.
High-speed MR spectroscopic imaging has important applications.
The development of hyperpolarized MRI agents presents both unprecedented opportunities and new technical challenges. In particular, with signal-to-noise ratio (SNR) enhancements on the order of the 10000-fold, dynamic nuclear polarization of metabolically active substrates (e.g., 13C-labeled pyruvate or acetate) theoretically permits in vivo imaging of not only the injected agent, but also downstream metabolic products. This feature of hyperpolarized MR spectroscopy (MRS) provides investigators a unique opportunity to non-invasively monitor critical dynamic metabolic processes in vivo under both normal and pathologic conditions. Important applications include tumor diagnosis and treatment monitoring, as well as assessment of cardiac function. In studies using hyperpolarized samples, the magnetization decays toward its thermal equilibrium value and is not recoverable. Therefore, fast spectroscopic imaging acquisition schemes are important.
A recent study by Golman et al. (37) described real-time metabolic imaging. NMR spectroscopy has until now been the only noninvasive method to gain insight into the fate of pyruvate in the body, but the low NMR sensitivity even at high field strength has only allowed information about steady-state conditions. The medically relevant information about the distribution, localization, and metabolic rate of the substance during the first minute after the injection has not been obtainable. Use of a hyperpolarization technique has enabled 10-15% polarization of 13C1 in up to a 0.3 Mpyruvate solution. i.v. injection of the solution into rats and pigs allows imaging of the distribution of pyruvate and mapping of its major metabolites lactate and alanine within a time frame of 10 s.
Hyperpolarized MRS is currently being developed by major manufacturers and expected to be of considerable commercial value.
MR spectroscopic imaging in moving organs, like the heart or the breast, is sensitive to movement artifact that results in blurring of the image. Gating to the heart beat is frequently used to reduce motion artifact, but this reduces data acquisition efficiency. Simultaneous synchronization to respiration may be required to further reduce motion artifacts, which additionally reduces data acquisition efficiency. Gating in the presence of irregular heart beat introduces variability in repetition time that results in non steady-state signal intensity and distortion of the image encoding process. Image registration during post-processing is challenging due to the highly nonlinear movement pattern within the chest. High-speed spectroscopic imaging acquisition schemes considerably reduce motion sensitivity.
MR spectroscopic imaging in organs, like the brain, is sensitive to localized signal fluctuations due to blood pulsation or other physiological movement mechanisms (e.g. CSF movement) that results in blurring of the image. Gating to the rhythm of the physiological fluctuation (e.g. heart beat) can be used to reduce this artifact, but this reduces data acquisition efficiency. Gating in the presence of irregular heart beat introduces variability in repetition time that results in non steady-state signal intensity and distortion of the image encoding process. Therefore, fast spectroscopic imaging acquisition schemes are important.
Functional MRI is widely used to map changes in brain activation in animals and humans. However, the methodology lacks quantification due complex interdependence of the signal changes on blood flow, blood volume, oxygen extraction, vascular architecture and other factors. It also suffers from sensitivity to macroscopic off-resonance effects resulting from macroscopic magnetic field inhomogeneity and it is sensitive to physiological fluctuations (e.g. heart beat related blood pulsation) and movement. Furthermore, the widely used echo-planar-imaging (EPI) technique additionally suffers from image ghosting due to interference of signals acquired with opposite readout gradient polarity, which makes phase sensitive image reconstruction difficult. In our early work we have introduced PEPSI as a method to map the change in water spectra during functional brain activation (38), which however had limited temporal resolution. More recently we used multi-echo EPI (39), which enables quantitative mapping of T2*, but like all EPI based techniques suffers from ghosting artifacts and is thus not suitable for quantitative phase sensitive mapping. Fast and phase sensitive spectroscopic mapping of the water relaxation decay has the potential to provide considerably improve quantification of functional MRI, since the time course and phase of the decaying signal carry information about the blood volume, the blood vessel diameter distribution and intra-vascular signals in larger blood vessels (40,41). Fast acquisition speed is also important to reduce the influence of physiological fluctuations and movement.
This method is also applicable to spatial mapping chemical reactions for applications in material science and biology. For example, the spatial evolution of a chemical chain reaction could be observed. Such reactions are typically very fast and fast spectroscopic imaging acquisition schemes are thus important to avoid blurring of the spectroscopic images.